There are many instances in which it is useful to identify from a large set of items one or more subsets of related items. In addition, it is often useful to assign a “tag” to a subset of related items, which indicates a manner in which the items are related. Tags can be selected to have a semantic meaning, providing a mechanism for humans to understand the nature of the subsets and select subsets for specific reasons.
Identification of subsets of items, and tagging of items or subsets, may occur, for example, in connection with social networks or other computer systems that are accessible to large numbers of people. Subsets of people with a common interest may be identified. The resulting subsets may have tags that allow other users of the system to determine whether they share a common interest with the identified subsets. In this way, people sharing common interests can connect using computer-based communications supported by the social networking system.
Though, identifying subsets and applying tags can occur in other contexts and involving items other than people. For example, in some social networking systems users post photographs or other items potentially of interest to other users. These items may be tagged to indicate their content in a human-understandable form, allowing users to search for items related to a particular topic or to find subsets of related items.
In some instances, tags are first assigned to items such that they can then be segregated into subsets based on the tags. In such scenarios, tags are assigned manually. Though, assigning tags manually can be time consuming or inaccurate because different users may tag related items differently. It is also known to first identify subsets of related items and then assign tags to the subsets in either in an automated or manual fashion. Automated processing to identify subsets of related items is sometimes called “clustering.”